FitBuddy - Food Tracking & Diet Planning App

A full-stack web application (PWA) for tracking food intake, analyzing nutrients, and generating personalized diet recommendations using AI.

Features

• 🍽️ Food Logging: Log your meals by time (morning, afternoon, evening)
• 🤖 AI-Powered Analysis: Automatic nutrient breakdown (calories, protein, carbs, fats, fiber)
• 📊 Daily Summaries: Get AI-generated summaries of your daily food intake
• 🎯 Personalized Diet Plans: After 3-4 days of logging, receive personalized recommendations
• 🔄 Food Replacements: Get suggestions to replace high-calorie, low-nutrition foods with better alternatives
• 📱 PWA Support: Install as a mobile app on iOS and Android

Tech Stack

Frontend

• Next.js 16 (App Router)
• TypeScript
• Tailwind CSS
• PWA (Progressive Web App)

Backend

• FastAPI (Python)
• SQLAlchemy (ORM)
• SQLite/PostgreSQL (Database)
• OpenAI GPT-4 (AI Analysis)

Project Structure

FitBuddy/
├── frontend/          # Next.js frontend application
│   ├── app/          # Next.js app directory
│   ├── components/   # React components
│   ├── lib/          # API utilities
│   └── public/       # Static assets
├── backend/          # FastAPI backend application
│   ├── app/
│   │   ├── routers/  # API route handlers
│   │   ├── services/ # Business logic (AI service)
│   │   ├── models.py # Database models
│   │   └── schemas.py # Pydantic schemas
│   └── requirements.txt
└── README.md

Setup Instructions

Prerequisites

• Node.js 18+ and npm
• Python 3.9+
• OpenAI API key

Backend Setup

1. Navigate to the backend directory:

cd backend

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Create a .env file:

cp .env.example .env

5. Update .env with your configuration:

DATABASE_URL=sqlite:///./fitbuddy.db
OPENAI_API_KEY=your_openai_api_key_here
SECRET_KEY=your_secret_key_here

6. Run the backend server:

uvicorn app.main:app --reload

The API will be available at http://localhost:8000 API documentation: http://localhost:8000/docs

Frontend Setup

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Create a .env.local file (optional, defaults to localhost:8000):

NEXT_PUBLIC_API_URL=http://localhost:8000

4. Run the development server:

npm run dev

The app will be available at http://localhost:3000

Building for Production

Frontend:

cd frontend
npm run build
npm start

Backend:

cd backend
uvicorn app.main:app --host 0.0.0.0 --port 8000

Usage

1. Log Food: Select a date and meal time, then describe what you ate
2. Analyze: Click "Analyze Nutrients" on any food log to get detailed nutritional information
3. View Summary: See daily summaries and total nutrients for each day
4. Generate Diet Plan: After logging food for 3-4 days, go to the "Diet Plan" tab and click "Generate Plan" to get personalized recommendations

API Endpoints

Food Logs

• POST /api/food-logs/ - Create a food log
• GET /api/food-logs/ - Get all food logs (optional date query parameter)
• GET /api/food-logs/{id} - Get a specific food log
• PUT /api/food-logs/{id} - Update a food log
• DELETE /api/food-logs/{id} - Delete a food log

AI Analysis

• POST /api/ai/analyze - Analyze a food log and extract nutrients
• POST /api/ai/summarize - Get daily food summary
• GET /api/ai/nutrients/{date} - Get total nutrients for a date

Diet Plan

• POST /api/diet-plan/generate - Generate a personalized diet plan
• GET /api/diet-plan/ - Get the latest diet plan

PWA Installation

1. Open the app in a mobile browser (Chrome, Safari)
2. Look for the "Add to Home Screen" prompt or use the browser menu
3. The app will be installed and can be used offline (with cached data)

Development

Adding New Features

• Backend: Add new routes in backend/app/routers/
• Frontend: Add new components in frontend/components/
• AI Service: Modify backend/app/services/ai_service.py for AI-related changes

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.